Boston University

Questrom School of Business

595 Commonwealth Avenue, Boston, MA 02215

Email: haoxing@bu.edu

Curriculum Vitae 

Research

Stochastic Control and its applications in Mathematical Finance and Financial Economics

Working paper

We develop a dynamic principal-agent model in which conditioning future pay- for-performance on monitoring signals is a perfect substitute for contemporaneous pay-for-performance in providing incentives. Average pay-for-performance is higher when monitoring is less efficient, because the conditioning is a less effective substitute in that case. Monitoring efficiency has a greater effect on pay-for-performance when negative signals have accumulated. Using changes in the availability of direct fights for board directors to a firm's headquarters as an exogenous shock to monitoring, we present new empirical evidence on the monitoring-compensation linkage that supports the model’s predictions. 

We examine optimal dynamic contracts when the firm's production generates harmful pollution undermining its productivity. The optimal contract rewards for financial performance and penalizes pollution. The combination of both contract sensitivities incentivizes the agent's effort and environmental (pollution abating) investment. In an economy with a continuum of polluting firms, contracting on firm pollution improves the welfare of the principal and the agent. Calibrating the model to the U.S. economy, we show that the aggregated pollution is reduced by 38.4% if all firms contract on their own pollution.

We reveal and study a new empirical fact: Executive and skilled labor pay is increasing in firm process intensity (the fraction of intangibles used to improve the efficiency of the firm). We rationalize this fact in a dynamic principal-agent model. The optimal contract reveals a direct and indirect effect of process intensity on compensation. We verify these effects in the data. In our baseline specification, a one standard deviation increase in process intensity is associated with an 8% increase in executive pay and a 3% increase in skilled labor wages relative to industry peers. 

We study aversion to model ambiguity and misspecification in dynamic portfolio choice. Investors with relative risk aversion gamma > 1 fear return persistence, while risk-tolerant investors (0 < gamma < 1) fear return mean reversion, to confront model misspecification concerns when facing a model with IID returns.  Our model can explain evidence for the experience hypothesis, for nonparticipation in equity markets, as well as for extrapolative return expectations. 

Best paper in Corporate Finance, Southwestern Finance Association Annual Meeting 2023

A firm's policy for cash holdings balances the motives for investment and precautionary savings. The relative importance of these motives changes as a firm's size changes. 

Heterogeneous learning abilities among consumers introduce inefficiency to competitive online product markets. Inefficiency emerges due to a learning externality generated by consumers with inferior learning ability.

Dynamic sentiment arise endogenously due to agents’ attitude toward alternative models. Distorted beliefs generate countercyclical risk aversion, procyclical portfolio weights, countercyclical equilibrium asset returns, and excess volatility.

Forthcoming

to appear in Economic Theory

We adopt the posterior-based approach to study dynamic discrete choice problems under rational inattention. We provide necessary and sufficient conditions to characterize the solution for general uniformly posterior-separable cost functions. 

The following package provides an efficient algorithm to solve multiple states and long horizon dynamic discrete choice problem [Package]

to appear in Journal of Finance

We develop an intertemporal equilibrium model to examine how circuit breakers impact the behavior of prices, trading, and welfare. We show that as the price approaches the circuit breaker, its volatility rises drastically, accelerating the chance of triggering the circuit breaker – the so-called “magnet effect”. In addition, returns exhibit increasing negative skewness and positive drift, while trading activity spikes up. Our empirical analysis confirms these predictions. Moreover, we show that a circuit breaker can affect the overall welfare either negatively or positively, depending on the relative significance of investors’ trading motives for risk sharing vs. irrational speculation.

to appear in Management Science

Principal of a firm manages the firm termination risk by loading the contract with a positive market component which alleviates termination risk in normal market conditions, but makes termination more likely after negative shocks.

Annals of Applied Probability,  32(5): 3492-3536, 2022

We present a backward uniqueness result to study the nodal set of Z for a system of BSDEs. Using this result, we prove the existence of an incomplete Radner equilibrium with nondegenerate endogenous volatility in a continuous-time stochastic model of an endowment economy.

Publications 

Stochastic Analysis, Filtering, and Stochastic Optimization: A Commemorative Volume to Honor Mark H. A. Davis's Contributions, 267-292, 2022, [Publisher version] 

Risk Magazine, cutting edge session, 2019, [Journal] [Extended version] [Presentation] 

Journal of Economic Theory, 173:142-180, 2018. [SSRN]

Annals of Probability, 46(1):491-550, 2018. [Arxiv] [Presentation]

Mathematical Finance, 28: 991-1019, 2018. [SSRN] 

Annales de l'Institut Henri Poincaré (B), 53(4):1528-1547, 2017. [Arxiv] 

Finance and Stochastics, 21(1):227-262, 2017. [SSRN] 

SIAM Journal on Financial Mathematics, 8:400-434, 2017. [Arxiv]

Mathematical Finance, 27:38-67,2017. [Arxiv]

Mathematical Finance, 27:3-37, 2017. [SSRN]

SIAM Journal on Financial Mathematics, 6(1):242-280, 2015. [Arxiv]

SIAM Journal on Control and Optimization, 53(1):185-212, 2015. [Arxiv]

Finance and Stochastics, 18(1):75-114, 2014. [Arxiv]

Electronic Journal of Probability, 18:26, 2013. [Arxiv]

Stochastic Processes and their Applications, 122(8):2961-2993, 2012. [Arxiv]

SIAM Journal on Control and Optimization, 50(3):1337-1357, 2012. [Arxiv]

Stochastic Processes and their Applications, 122:2265-2291, 2012. [Arxiv]

SIAM Journal on Financial Mathematics, 3:351-373, 2012. [Arxiv]

Finance and Stochastics, 16:275-291, 2012. [Arxiv]

Mathematical Finance, 21(1):117-143, 2011. [Arxiv]

Proceedings of the American Mathematical Society, 138(6): 2061-2064, 2010. [Arxiv]

SIAM Journal on Mathematical Analysis, 41(2): 825-860, 2009. [Arxiv]

Mathematical Methods of Operations Research, 70(3): 505-525, 2009. [Arxiv]

Proceeding of the Fourth IASTED International Conference on Financial Engineering and Applications, 2007.


Teaching

Welcome applications to 

Fundamentals of Finance MF702 

Fixed Income Securities MF728

Portfolio Theory MF730

Advanced Machine Learning Applications for Finance MF815

Algorithmic and High Frequency Trading MF821